scholarly journals THE ANALYSIS OF APPROACHES TO MEASUREMENT UNCERTAINTY EVALUATION FOR CALIBRATION

2019 ◽  
Vol 9 (3) ◽  
pp. 26-29
Author(s):  
Sarsenbek Zhussupbekov ◽  
Lida Ibrayeva ◽  
Sarsenbek Zhussupbekov
Keyword(s):  
Monte Carlo ◽  
Measurement Uncertainty ◽  
Uncertainty Estimation ◽  
Estimation Result ◽  
Flow Meters ◽  
Uncertainty In Measurement ◽  
Advantages And Disadvantages ◽  
Measurement Uncertainty Evaluation ◽  
Measurement Uncertainty Estimation ◽  
Expression Of Uncertainty

A comparative analysis of the measurement uncertainty estimation result is carried out. The results are obtained by GUM method described in the Guide to the expression of uncertainty in measurement, as well as by Monte-Carlo method recommended in Supplement 1 to the Guide. Examples of calculations of uncertainty of relative error for electromagnetic flow meters calibration by two methods are given. The features of application, advantages and disadvantages of these methods are described.

Interpretation and use of standard atomic weights (IUPAC Technical Report)

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Adriaan M. H. van der Veen ◽  
Juris Meija ◽  
Antonio Possolo ◽  
David Brynn Hibbert
Keyword(s):  
Monte Carlo ◽  
Atomic Weight ◽  
Standard Uncertainty ◽  
Uncertainty In Measurement ◽  
Propagation Of Uncertainty ◽  
A Value ◽  
The Monte Carlo Method ◽  
Technical Report ◽  
Molecular Masses ◽  
Expression Of Uncertainty

Abstract Many calculations for science or trade require the evaluation and propagation of measurement uncertainty. Although relative atomic masses (standard atomic weights) of elements in normal terrestrial materials and chemicals are widely used in science, the uncertainties associated with these values are not well understood. In this technical report, guidelines for the use of standard atomic weights are given. This use involves the derivation of a value and a standard uncertainty from a standard atomic weight, which is explained in accordance with the requirements of the Guide to the Expression of Uncertainty in Measurement. Both the use of standard atomic weights with the law of propagation of uncertainty and the Monte Carlo method are described. Furthermore, methods are provided for calculating uncertainties of relative molecular masses of substances and their mixtures. Methods are also outlined to compute material-specific atomic weights whose associated uncertainty may be smaller than the uncertainty associated with the standard atomic weights.

ISO/TS 20914:2019 – a critical commentary

2020 ◽  
Vol 58 (8) ◽  
pp. 1182-1190 ◽  
Author(s):  
Ian Farrance ◽  
Robert Frenkel ◽  
Tony Badrick
Keyword(s):  
Measurement Uncertainty ◽  
Measurement Data ◽  
International Normalized Ratio ◽  
Medical Laboratory ◽  
Uncertainty In Measurement ◽  
Medical Laboratories ◽  
Functional Relationships ◽  
Critical Commentary ◽  
Combined Uncertainty ◽  
Expression Of Uncertainty

AbstractThe long-anticipated ISO/TS 20914, Medical laboratories – Practical guidance for the estimation of measurement uncertainty, became publicly available in July 2019. This ISO document is intended as a guide for the practical application of estimating uncertainty in measurement (measurement uncertainty) in a medical laboratory. In some respects, the guide does indeed meet many of its stated objectives with numerous very detailed examples. Even though it is claimed that this ISO guide is based on the Evaluation of measurement data – Guide to the expression of uncertainty in measurement (GUM), JCGM 100:2008, it is with some concern that we believe several important statements and statistical procedures are incorrect, with others potentially misleading. The aim of this report is to highlight the major concerns which we have identified. In particular, we believe the following items require further comment: (1) The use of coefficient of variation and its potential for misuse requires clarification, (2) pooled variance and measurement uncertainty across changes in measuring conditions has been oversimplified and is potentially misleading, (3) uncertainty in the results of estimated glomerular filtration rate (eGFR) do not include all known uncertainties, (4) the international normalized ratio (INR) calculation is incorrect, (5) the treatment of bias uncertainty is considered problematic, (6) the rules for evaluating combined uncertainty in functional relationships are incomplete, and (7) specific concerns with some individual statements.

A Simplified Software for Uncertainty Estimation Using Monte Carlo Method

2020 ◽  
Vol 12 (8) ◽  
pp. 1050-1053
Author(s):  
Jasveer Singh ◽  
L. A. Kumaraswamidhas ◽  
Neha Bura ◽  
Kapil Kaushik ◽  
Nita Dilawar Sharma
Keyword(s):  
Monte Carlo ◽  
Standard Deviation ◽  
Monte Carlo Method ◽  
Measurement Uncertainty ◽  
Standard Uncertainty ◽  
Uncertainty Estimation ◽  
End Points ◽  
The Monte Carlo Method ◽  
Adaptive Trials ◽  
Coverage Interval

The current paper discusses about the application of Monte Carlo method for the evaluation of measurement uncertainty using in-house developed program on C++ platform. The Monte Carlo method can be carried out by fixed trials as well as adaptive trials using this program. The program provides the four parameters viz. estimate of measurand, standard uncertainty in the form of standard deviation and end points of coverage interval as an output.

Measuring Uncertainty Using Different Approaches: A Case Study for Acetaminophen Quantification

2016 ◽  
Vol 99 (3) ◽  
pp. 612-617 ◽  
Author(s):  
Fabiane Lacerda Francisco ◽  
Alessandro Morais Saviano ◽  
Felipe Rebello Lourenço
Keyword(s):  
Measurement Uncertainty ◽  
Uncertainty Estimation ◽  
Pharmaceutical Drug ◽  
Drug Products ◽  
Pharmaceutical Equivalence ◽  
Reproducibility Study ◽  
Repeatability And Reproducibility ◽  
Analytical Result ◽  
Measurement Uncertainty Estimation

Abstract Investigation of out-of-specification analytical results is laborious, time-consuming, and costly and must be well documented. However, an analytical result is not complete unless reported with its measurement uncertainty. Here, we compare four different approaches for measurement uncertainty estimation used in acetaminophen quantification in pharmaceutical drug products. Measurement uncertainties were estimated using a repeatability and reproducibility study, Eurachem/Citac guidelines, Monte Carlo simulations, and a spreadsheet method. These different approaches provided similar results. However, they differed by the sources of uncertainties considered, by the procedures of calculation, and by the effort required in routine applications. Nevertheless, all four approaches were successful in assessing conformity of acetaminophen content in pharmaceutical drug products and may be used in assessing pharmaceutical equivalence.

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